How to cite this paper
Hirzallah, M & Alshurideh, M. (2023). The effects of the internal and the external factors affecting artificial intelligence (AI) adoption in e-innovation technology projects in the UAE? Applying both innovation and technology acceptance theories.International Journal of Data and Network Science, 7(3), 1321-1332.
Refrences
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Achjari, D., & Quaddus, M. (2003). Roles of formal/informal networks and perceived compatibility in the diffusion of World Wide Web: The case of Indonesian banks. 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of The, 11-pp.
Agarwal, R., & Karahanna, E. (1998). On the multi-dimensional nature of compatibility beliefs in technology acceptance. Proceedings of the 19th Annual International Conference on Information Systems, 13–16.
Ahmad, H., Hanandeh, R., Alazzawi, F., Al-Daradkah, A., ElDmrat, A., Ghaith, Y., & Darawsheh, S. (2023). The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms. International Journal of Data and Network Science, 7(1), 35–40.
Al-Maroof, R. S., Alshurideh, M. T., Salloum, S. A., AlHamad, A. Q. M., & Gaber, T. (2021). Acceptance of Google Meet during the spread of Coronavirus by Arab university students. Informatics, 8(2), 24.
Al Kurdi, B., Alshurideh, M., Salloum, S. A., Obeidat, Z. M., & Al-dweeri, R. M. (2020). An Empirical Investigation into Examination of Factors Influencing University Students’ Behavior towards Elearning Acceptance Using SEM Approach. International Journal of Interactive Mobile Technologies (IJIM), 14(02), 19–41.
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110.
Ali Abbasi, G., Abdul Rahim, N. F., Wu, H., Iranmanesh, M., & Keong, B. N. C. (2022). Determinants of SME’s social media marketing adoption: competitive industry as a moderator. Sage Open, 12(1), 1-21.
Ali, M., Raza, S. A., Puah, C. H., & Amin, H. (2019). Consumer acceptance toward takaful in Pakistan: An application of diffusion of innovation theory. International Journal of Emerging Markets, 14(4), 620-638.
Alomari, M., Woods, P., & Sandhu, K. (2012). Predictors for e‐government adoption in Jordan: Deployment of an empirical evaluation based on a citizen‐centric approach. Information Technology & People, 25(2), 207-234.
Alosani, M. S., & Al-Dhaafri, H. S. (2023). Service innovation in government: evidence from the UAE. Management & Sustainability: An Arab Review.
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843–858.
Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2019). Examining the Main Mobile Learning System Drivers’ Effects: A Mix Empirical Examination of Both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). International Conference on Advanced Intelligent Systems and Informatics, 406–417.
Ashraf, A. R., Thongpapanl, N. (Tek), & Spyropoulou, S. (2016). The connection and disconnection between e-commerce businesses and their customers: Exploring the role of engagement, perceived usefulness, and perceived ease-of-use. Electronic Commerce Research and Applications, 20, 69–86.
Badi, S., Ochieng, E., Nasaj, M., & Papadaki, M. (2021). Technological, organisational and environmental determinants of smart contracts adoption: UK construction sector viewpoint. Construction Management and Economics, 39(1), 36–54.
Bagozzi, R. P., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34.
Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191.
Brown, I., Stothers, R., Thorp, S., & Ingram, L. (2006). The role of learning styles in the acceptance of web-based learning tools. 36th Annual Conference of the Southern African Computer Lecturers Association SACLA2006, 1(1), 189–200.
Carraher-Wolverton, C., & Zhu, Z. (2021). Faculty engagement in online education: applying the perceived characteristics of innovation to explain online teaching intention. Electronic Journal of E-Learning, 19(5), pp388-400.
Carter, L. (2008). E‐government diffusion: a comparison of adoption constructs. Transforming Government: People, Process and Policy, 2(3), 147–161.
Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021). Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technological Forecasting and Social Change, 170, 120880.
Chen, M.-P. (2009). An evaluation of the ELNP e-learning quality assurance program: Perspectives of gap analysis and innovation diffusion. Journal of Educational Technology & Society, 12(1), 18–33.
Chen, X., Fang, S., Li, Y., & Wang, H. (2019). Does identification influence continuous E-commerce consumption? The mediating role of intrinsic motivations. Sustainability, 11(7), 1944.
Chiu, H. H. (2018). Employees’ intrinsic and extrinsic motivations in innovation implementation: The moderation role of managers’ persuasive and assertive strategies. Journal of Change Management, 18(3), 218–239.
Christiansen, V., Haddara, M., & Langseth, M. (2022). Factors Affecting Cloud ERP Adoption Decisions in Organizations. Procedia Computer Science, 196, 255–262.
D’Attoma, I., & Ieva, M. (2020). Determinants of technological innovation success and failure: Does marketing innovation matter? Industrial Marketing Management, 91, 64–81.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487.
De Canio, F., Fuentes-Blasco, M., & Martinelli, E. (2022). Extrinsic motivations behind mobile shopping: what drives regular and occasional shoppers? International Journal of Retail & Distribution Management, ahead-of-print.
Demircioglu, M. A., & Chen, C.-A. (2019). Public employees’ use of social media: Its impact on need satisfaction and intrinsic work motivation. Government Information Quarterly, 36(1), 51–60.
Dulaimi, M. (2021). The climate of innovation in the UAE and its construction industry. Engineering, Construction and Architectural Management, 29(1), 141-164.
Fan, Y.-H., & Lin, T.-J. (2023). Identifying university students’ online academic help-seeking patterns and their role in Internet self-efficacy. The Internet and Higher Education, 56, 100893.
Fırat, M., Kılınç, H., & Yüzer, T. V. (2018). Level of intrinsic motivation of distance education students in e‐learning environments. Journal of Computer Assisted Learning, 34(1), 63–70.
Fuchs, C., Sting, F. J., Schlickel, M., & Alexy, O. (2019). The Ideator’s Bias: How Identity-Induced Self-Efficacy Drives Overestimation in Employee-Driven Process Innovation. Academy of Management Journal, 62(5), 1498–1522.
Gagné, M., & Deci, E. L. (2005). Self‐determination theory and work motivation. Journal of Organizational Behavior, 26(4), 331–362.
Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788-807.
Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The Effects of Perceived Usefulness and Perceived Ease of Use on Continuance Intention to Use E-Government. Procedia Economics and Finance, 35, 644–649.
Harandi, S. R. (2015). Effects of e-learning on Students’ Motivation. Procedia-Social and Behavioral Sciences, 181, 423–430.
Hasan, T., Kumar, S., Raghav, S., Tiwari, A., & Gautam, M. (2017). E-INNOVATION. Technology, 8(1), 86–93.
Hoang, T. D. L., & Nguyen, H. K. (2022). Towards an economic recovery after the COVID-19 pandemic: empirical study on electronic commerce adoption by small and medium-sized enterprises in Vietnam. Management & Marketing. Challenges for the Knowledge Society, 17(2), 98–119.
Huang, C.-Y., Wang, H.-Y., Yang, C.-L., & Shiau, S. J. H. (2020). A derivation of factors influencing the diffusion and adoption of an open-source learning platform. Sustainability, 12(18), 7532.
Huang, M.-H., & Rust, R. T. (2013). IT-related service: A multidisciplinary perspective. Journal of Service Research, 16(3), 251–258.
Joo, Y. J., Lim, K. Y., & Lim, E. (2014). Investigating the structural relationship among perceived innovation attributes, intention to use and actual use of mobile learning in an online university in South Korea. Australasian Journal of Educational Technology, 30(4).
KANNAN, V. (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega, 33(2), 153–162.
Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2014). Innovation adoption attributes: a review and synthesis of research findings. European Journal of Innovation Management, 17(3), 327-348.
Khan, M. U. H. (2019). Innovative UAE. Defence Journal, 23(5), 60.
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Koe, W.-L., & Sakir, N. A. (2020). The motivation to adopt e-commerce among Malaysian entrepreneurs. Organizations and Markets in Emerging Economies, 11(1), 189–202.
Kuester, S., Konya-Baumbach, E., & Schuhmacher, M. C. (2018). Get the show on the road: Go-to-market strategies for e-innovations of startups. Journal of Business Research, 83, 65–81.
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Lan, P., & Du, H. H. (2002). Challenges ahead E-innovation. Technovation, 22(12), 761–767.
Lean, O. K., Zailani, S., Ramayah, T., & Fernando, Y. (2009). Factors influencing intention to use e-government services among citizens in Malaysia. International Journal of Information Management, 29(6), 458–475.
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Lin, A., & Chen, N.-C. (2012). Cloud computing as an innovation: Perception, attitude, and adoption. International Journal of Information Management, 32(6), 533–540.
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Liu, I.-F., & Young, S. S.-C. (2017). An exploration of participative motivations in a community-based online English extensive reading contest with respect to gender
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Ali Abbasi, G., Abdul Rahim, N. F., Wu, H., Iranmanesh, M., & Keong, B. N. C. (2022). Determinants of SME’s social media marketing adoption: competitive industry as a moderator. Sage Open, 12(1), 1-21.
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Alomari, M., Woods, P., & Sandhu, K. (2012). Predictors for e‐government adoption in Jordan: Deployment of an empirical evaluation based on a citizen‐centric approach. Information Technology & People, 25(2), 207-234.
Alosani, M. S., & Al-Dhaafri, H. S. (2023). Service innovation in government: evidence from the UAE. Management & Sustainability: An Arab Review.
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843–858.
Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2019). Examining the Main Mobile Learning System Drivers’ Effects: A Mix Empirical Examination of Both the Expectation-Confirmation Model (ECM) and the Technology Acceptance Model (TAM). International Conference on Advanced Intelligent Systems and Informatics, 406–417.
Ashraf, A. R., Thongpapanl, N. (Tek), & Spyropoulou, S. (2016). The connection and disconnection between e-commerce businesses and their customers: Exploring the role of engagement, perceived usefulness, and perceived ease-of-use. Electronic Commerce Research and Applications, 20, 69–86.
Badi, S., Ochieng, E., Nasaj, M., & Papadaki, M. (2021). Technological, organisational and environmental determinants of smart contracts adoption: UK construction sector viewpoint. Construction Management and Economics, 39(1), 36–54.
Bagozzi, R. P., & Yi, Y. (2012). Specification, evaluation, and interpretation of structural equation models. Journal of the Academy of Marketing Science, 40(1), 8–34.
Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191.
Brown, I., Stothers, R., Thorp, S., & Ingram, L. (2006). The role of learning styles in the acceptance of web-based learning tools. 36th Annual Conference of the Southern African Computer Lecturers Association SACLA2006, 1(1), 189–200.
Carraher-Wolverton, C., & Zhu, Z. (2021). Faculty engagement in online education: applying the perceived characteristics of innovation to explain online teaching intention. Electronic Journal of E-Learning, 19(5), pp388-400.
Carter, L. (2008). E‐government diffusion: a comparison of adoption constructs. Transforming Government: People, Process and Policy, 2(3), 147–161.
Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021). Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technological Forecasting and Social Change, 170, 120880.
Chen, M.-P. (2009). An evaluation of the ELNP e-learning quality assurance program: Perspectives of gap analysis and innovation diffusion. Journal of Educational Technology & Society, 12(1), 18–33.
Chen, X., Fang, S., Li, Y., & Wang, H. (2019). Does identification influence continuous E-commerce consumption? The mediating role of intrinsic motivations. Sustainability, 11(7), 1944.
Chiu, H. H. (2018). Employees’ intrinsic and extrinsic motivations in innovation implementation: The moderation role of managers’ persuasive and assertive strategies. Journal of Change Management, 18(3), 218–239.
Christiansen, V., Haddara, M., & Langseth, M. (2022). Factors Affecting Cloud ERP Adoption Decisions in Organizations. Procedia Computer Science, 196, 255–262.
D’Attoma, I., & Ieva, M. (2020). Determinants of technological innovation success and failure: Does marketing innovation matter? Industrial Marketing Management, 91, 64–81.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487.
De Canio, F., Fuentes-Blasco, M., & Martinelli, E. (2022). Extrinsic motivations behind mobile shopping: what drives regular and occasional shoppers? International Journal of Retail & Distribution Management, ahead-of-print.
Demircioglu, M. A., & Chen, C.-A. (2019). Public employees’ use of social media: Its impact on need satisfaction and intrinsic work motivation. Government Information Quarterly, 36(1), 51–60.
Dulaimi, M. (2021). The climate of innovation in the UAE and its construction industry. Engineering, Construction and Architectural Management, 29(1), 141-164.
Fan, Y.-H., & Lin, T.-J. (2023). Identifying university students’ online academic help-seeking patterns and their role in Internet self-efficacy. The Internet and Higher Education, 56, 100893.
Fırat, M., Kılınç, H., & Yüzer, T. V. (2018). Level of intrinsic motivation of distance education students in e‐learning environments. Journal of Computer Assisted Learning, 34(1), 63–70.
Fuchs, C., Sting, F. J., Schlickel, M., & Alexy, O. (2019). The Ideator’s Bias: How Identity-Induced Self-Efficacy Drives Overestimation in Employee-Driven Process Innovation. Academy of Management Journal, 62(5), 1498–1522.
Gagné, M., & Deci, E. L. (2005). Self‐determination theory and work motivation. Journal of Organizational Behavior, 26(4), 331–362.
Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788-807.
Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The Effects of Perceived Usefulness and Perceived Ease of Use on Continuance Intention to Use E-Government. Procedia Economics and Finance, 35, 644–649.
Harandi, S. R. (2015). Effects of e-learning on Students’ Motivation. Procedia-Social and Behavioral Sciences, 181, 423–430.
Hasan, T., Kumar, S., Raghav, S., Tiwari, A., & Gautam, M. (2017). E-INNOVATION. Technology, 8(1), 86–93.
Hoang, T. D. L., & Nguyen, H. K. (2022). Towards an economic recovery after the COVID-19 pandemic: empirical study on electronic commerce adoption by small and medium-sized enterprises in Vietnam. Management & Marketing. Challenges for the Knowledge Society, 17(2), 98–119.
Huang, C.-Y., Wang, H.-Y., Yang, C.-L., & Shiau, S. J. H. (2020). A derivation of factors influencing the diffusion and adoption of an open-source learning platform. Sustainability, 12(18), 7532.
Huang, M.-H., & Rust, R. T. (2013). IT-related service: A multidisciplinary perspective. Journal of Service Research, 16(3), 251–258.
Joo, Y. J., Lim, K. Y., & Lim, E. (2014). Investigating the structural relationship among perceived innovation attributes, intention to use and actual use of mobile learning in an online university in South Korea. Australasian Journal of Educational Technology, 30(4).
KANNAN, V. (2005). Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega, 33(2), 153–162.
Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2014). Innovation adoption attributes: a review and synthesis of research findings. European Journal of Innovation Management, 17(3), 327-348.
Khan, M. U. H. (2019). Innovative UAE. Defence Journal, 23(5), 60.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Koe, W.-L., & Sakir, N. A. (2020). The motivation to adopt e-commerce among Malaysian entrepreneurs. Organizations and Markets in Emerging Economies, 11(1), 189–202.
Kuester, S., Konya-Baumbach, E., & Schuhmacher, M. C. (2018). Get the show on the road: Go-to-market strategies for e-innovations of startups. Journal of Business Research, 83, 65–81.
Lan, P. (2004). Three new features of innovation brought about by information and communication technology. International Journal of Information Technology and Management, 3(1), 3–19.
Lan, P., & Du, H. H. (2002). Challenges ahead E-innovation. Technovation, 22(12), 761–767.
Lean, O. K., Zailani, S., Ramayah, T., & Fernando, Y. (2009). Factors influencing intention to use e-government services among citizens in Malaysia. International Journal of Information Management, 29(6), 458–475.
Lee, Y.-H., Hsieh, Y.-C., & Hsu, C.-N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use e-learning systems. Journal of Educational Technology & Society, 14(4), 124–137.
Liang, S., & Lu, H. (2013). Adoption of e‐government services: an empirical study of the online tax filing system in Taiwan. Online Information Review, 37(3), 424-442.
Lin, A., & Chen, N.-C. (2012). Cloud computing as an innovation: Perception, attitude, and adoption. International Journal of Information Management, 32(6), 533–540.
Liu, I.-F. (2020). The impact of extrinsic motivation, intrinsic motivation, and social self-efficacy on English competition participation intentions of pre-college learners: Differences between high school and vocational students in Taiwan. Learning and Motivation, 72, 101675.
Liu, I.-F., & Young, S. S.-C. (2017). An exploration of participative motivations in a community-based online English extensive reading contest with respect to gender
Liu, S.-H., Liao, H.-L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599–607.
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